---
title: "Step 1: Assembling occurrence records and biome schemes"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Step 1: Assembling occurrence records and biome schemes}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include=FALSE}
# Cap BLAS / OpenMP threads to 1 for the vignette build (avoids a
# non-deterministic OpenBLAS allocation error on Windows with R >= 4.6 during
# the raster extracts behind biomes_classify() / biomes_rank()).
Sys.setenv(OPENBLAS_NUM_THREADS = "1")
Sys.setenv(OMP_NUM_THREADS      = "1")

knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
library(biomes)
data(biomes_example)

# Chunks that need the ~36 MB biome raster run only when it can be fetched
# without burdening CRAN.
run_raster <- isTRUE(as.logical(Sys.getenv("NOT_CRAN", "false")))
if (run_raster) {
  run_raster <- tryCatch({ biomes_download(quiet = TRUE); TRUE },
                         error = function(e) FALSE)
}
```

# The four-step biomes workflow

`biomes` follows a four-step workflow, mirrored by these four vignettes and by
Figure 1 of the companion paper:

1. **Assembling occurrence records and biome schemes** *(this vignette)*.
2. [Choosing a biome scheme](step2-choosing-a-biome-scheme.html).
3. [Occurrences-to-biome classification](step3-occurrence-to-biome-classification.html).
4. [Output and visualisation](step4-output-and-visualisation.html).

Throughout, we use the packaged example dataset `biomes_example` so you can run
everything without a download.

> **Terms.** A **biome scheme** is one of the 31 published classification systems.
> A **biome class** is a category within a scheme (e.g. *savanna*). A **biome scheme
> number** (1-31) identifies a scheme; it is the value you pass to the `scheme`
> argument of the classification and visualisation functions.

---

# 1. Occurrence records

Every downstream function works on a **table of occurrence records**, one row per
record, with a **longitude** and a **latitude** column in **decimal degrees,
WGS84 (EPSG:4326)**. You may also pass an `sf` object or a `terra::SpatVector`.

| Column | Required | Notes |
|--------|----------|-------|
| longitude | yes | numeric, decimal degrees, WGS84. Default name `decimalLongitude`. |
| latitude  | yes | numeric, decimal degrees, WGS84. Default name `decimalLatitude`. |
| `species` | for species counts | needed only to count species per biome class (Step 4). |
| anything else | no | carried through untouched. |

If your columns are named differently, pass their names via `lon` and `lat`:

```{r, eval = FALSE}
biomes_rank(occ, lon = "decimallongitude", lat = "decimallatitude")
```

The packaged example set:

```{r}
data(biomes_example)
nrow(biomes_example)
head(biomes_example)
```

If you do not already have a dataset, `biomes_occ()` can download and clean one from
GBIF for a taxon (needs the `rgbif` / `CoordinateCleaner` packages and a network
connection):

```{r, eval = FALSE}
occ <- biomes_occ(taxon = "Fagus sylvatica")
```

---

# 2. The 31 biome schemes

`biomes_get()` returns the packaged raster stack: 31 biome schemes at 10 × 10 km,
globally.

```{r, eval = run_raster}
schemes <- biomes_get()
schemes
```

Each layer of the stack matches one row of `biomes_information`, in the same order.
Use it (or the human-readable `biomes_info()`) to see which publication and
methodology a scheme comes from:

```{r}
data(biomes_information)
biomes_information[25, c("publication", "name_of_classification",
                         "scheme_type", "scheme_number")]

biomes_info(25)   # readable summary for biome scheme no. 25
```

> **Scheme numbering.** Biome scheme numbers follow the order of the biome inventory
> of Fischer et al. (2022), i.e. the alphabetical order of the 31 schemes' original
> publications. Scheme no. 25, for example, is the vegetation scheme of Ramankutty
> & Foley (1999).

The class-level lookup (raster value → biome-class name, per scheme) lives in
`biomes_legend`; the classification and visualisation functions use it internally.

---

# Next

You now have (a) occurrence records and (b) the 31 biome schemes and their metadata.
Continue with [Step 2: Choosing a biome scheme](step2-choosing-a-biome-scheme.html).
